Assessment of cerebral autoregulation from ectopic heartbeats

The INfoMATAS project: Methods for assessing cerebral autoregulation in stroke

Cerebral autoregulation refers to the physiological mechanism that aims to maintain blood flow to the brain approximately constant when blood pressure changes. Impairment of this protective mechanism has been linked to a number of serious clinical conditions, including carotid stenosis, head trauma, subarachnoid haemorrhage and stroke. While the concept and experimental evidence is well established, methods for the assessment of autoregulation in individual patients remains an open challenge, with no gold-standard having emerged. In the current review paper, we will outline some of the basic concepts of autoregulation, as a foundation for experimental protocols and signal analysis methods used to extract indexes of cerebral autoregulation. Measurement methods for blood flow and pressure are discussed, followed by an outline of signal pre-processing steps. An outline of the data analysis methods is then provided, linking the different approaches through their underlying principles and rationale. The methods cover correlation based approaches (e.g. Mx) through Transfer Function Analysis to non-linear, multivariate and time-variant approaches. Challenges in choosing which method may be 'best' and some directions for ongoing and future research conclude this work.

The Effect of Data Length on the Assessment of Dynamic Cerebral Autoregulation with Transfer Function Analysis in Neurological ICU Patients

Background

Cerebral autoregulation plays an important role in safeguarding adequate cerebral perfusion and reducing the risk of secondary brain injury, which is highly important for patients in the neurological intensive care unit (neuro-ICU). Although the consensus white paper suggests that a minimum of 5 min of data are needed for assessing dynamic cerebral autoregulation with transfer function analysis (TFA), it remains unknown if the length of these data is valid for patients in the neuro-ICU, of whom are notably different than the general populations. We aimed to investigate the effect of data length using transcranial Doppler ultrasound combined with invasive blood pressure measurement for the assessment of dynamic cerebral autoregulation in patients in the neuro-ICU.

Methods

Twenty patients with various clinical conditions (severe acute encephalitis, ischemic stroke, subarachnoid hemorrhage, brain injury, cerebrovascular intervention operation, cerebral hemorrhage, intracranial space-occupying lesion, and toxic encephalopathy) were recruited for this study. Continuous invasive blood pressure, with a pressure catheter placed at the radial artery, and bilateral continuous cerebral blood flow velocity with transcranial Doppler ultrasound were simultaneously recorded for a length of 10 min for each patient. TFA was applied to derive phase shift, gain, and coherence function at all frequency bands from the first 2, 3, 4, 5, 6, 7, 8, 9, and 10 min of the 10-min recordings in each patient on both hemispheres. The variability in the autoregulatory parameters in each hemisphere was investigated by repeated measures analysis of variance.

Results

Forty-one recordings (82 hemispheres) were included in the study. According to the critical values of coherence provided by the Cerebral Autoregulation Research Network white paper, acceptable rates for the data were 100% with a length ≥ 7 min. The final analysis included 68 hemispheres. The effects of data length on trends in phase shift in the very low frequency (VLF) band (F_{1.801,120.669} = 6.321, P = 0.003), in the LF band (F_1.274,85.343 = 4.290, P = 0.032), and in the HF band (F_1.391,93.189 = 3.868, P = 0.039) were significant for 3–7 min, for 4–7 min, and for 5–8 min, respectively. Effects were also significant on the gain in the VLF band (F_{1.927,129.134} = 3.215, P = 0.045) for 2–8 min and on the coherence function in all frequency bands (VLF F_{2.846,190.671} = 90.247, P < 0.001, LF F_{2.515,168.492} = 55.770, P < 0.001, HF F_{2.411, 161.542} = 33.833, P < 0.001) for 2–10 min.

Conclusions

Considering the acceptable rates for the data and the variation in the TFA variables (phase shift and gain), we recommend recording data for a minimum length of 7 min for TFA in patients in the neuro-ICU.

Can we assess dynamic cerebral autoregulation in stroke patients with high rates of cardiac ectopicity?

It is unclear whether physiological recordings containing high numbers of ectopic heartbeats can be used to measure the cerebral autoregulation (CA) of blood flow. This study evaluated the utility of such data for assessing dynamic CA capacity. Physiological recordings of cerebral blood flow velocity, heart rate, end-tidal CO₂ and beat-to-beat blood pressure from acute ischaemic stroke (AIS) patients (n = 46) containing ectopic heartbeats of varying number (0.2 to 25 occurrences per minute) were analysed. Dynamic CA was determined using the autoregulation index (ARI) and the normalised mean square error (NMSE) was used to evaluate the fitting of the step response between BP and CBFV to Tiecks' model. We fitted linear mixed models on the CA variables incorporating ectopic burden, age, sex and hemisphere as predictor variables. Ectopic activity demonstrated an association with mean coherence (p = 0.006) but not with ARI (p = 0.162), impaired CA based on dichotomised ARI (p = 0.859) or NMSE (p = 0.671). Dynamic CA could be reliably assessed in AIS patients using physiological recordings with high rates of cardiac ectopic activity. This provides supportive data for future studies evaluating CA capability in AIS patients, with the potential to develop more individualised treatment strategies. Graphical Abstract.

The effect of blood pressure calibrations and transcranial Doppler signal loss on transfer function estimates of cerebral autoregulation

There are methodological concerns with combined use of transcranial Doppler (TCD) and Finapres to measure dynamic cerebral autoregulation. The Finapres calibration mechanism ("physiocal") causes interruptions to blood pressure recordings. Also, TCD is subject to signal loss due to probe movement. We assessed the effects of "physiocals" and TCD signal loss on transfer function estimates in recordings of 45 healthy subjects. We added artificial "physiocals" and removed sections of TCD signal from 5 min Finapres and TCD recordings. We also compared transfer function results from 5 min time series with time series as short as 1 min. Accurate transfer function estimates can be achieved in the 0.03-0.07 Hz band using beat-by-beat data with linear interpolation, while data loss is less than 10s. At frequencies between 0.07 and 0.5 Hz, transfer function estimates become unreliable with 5s of data loss every 50s. 2s data loss only affects frequency bands above 0.15Hz. Finally, accurate transfer function assessment of autoregulatory function can be achieved from time series as short as 1min, although gain and coherence tend to be overestimated at higher frequencies.